You will learn how to set up a simulation for large molecules (proteins and peptides) in PK-Sim, export it to Mobi, implement a Target-Mediated Drug Disposition (TMDD) model, generate a tumor compartment and link its volume to a tumor growth model. This is all demonstrated in the context of a model for antibody-drug conjugate (ADC) PK and PD, which also requires intracellular payload release, payload distribution and metabolism. The modeled compound is an ADC applied for the treatment of prostate cancer. The ADC consists of an antibody against the transmembrane protein TenB2 (TMEFF2) and the antimitotic toxin monomethyl auristatin E (MMAE), which is attached to the antibody by a linker. The antibody in the ADC has high affinity to the TMEFF2 receptor making it a suitable substance to target prostate cancer cells over-expressing TMEFF2, while the MMAE toxin is used to neutralize/kill such cancer cells.

You will set up a combined model for the simulation of the ADC and the released toxophore (i.e. the MMAE toxin) including receptor dynamics and internalization of the ADC-receptor complex. Here, you will learn how to:
1. Start a large molecule simulation in PK-Sim
2. Export a PK-Sim model to MoBi.
3. Integrate the TMDD reactions for receptor dynamics and internalization of the ADC-TMEFF2 complex (import “ReactionsADCModel.pkml).
4. Generate a tumor organ from a clone of another organ (muscle)
5. Make the tumor volume change over time according to an existing tumor growth model
6. Simulate, compare with observed data and refine the simulations by parameter identification
7. Add dosing of the naked (unconjugated) antibody and see how it affects tumor growth and toxophore release in different tissues

Based on:
Boswell, C. Andrew, et al. "An integrated approach to identify normal tissue expression of targets for antibody‐drug conjugates: case study of TENB2." British journal of pharmacology vol. 168,2 (2013): 445-457.